Category Archives: aging.ai

Which Blood Test Analyte Is Most Important For Predicting Biologic Age?

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Three studies have investigated the ability of blood test analytes to predict biological age. First, when considering the top 20 variables that were associated with biological age in aging.ai, albumin contributed most to this prediction, almost 2x more than circulating levels of glucose (Mamoshina et al. 2018):

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Second, albumin was one of the 9 blood test variables that were best able to predict biological age when using the Phenotypic Age calculator.  However, as shown below, it didn’t come in first place, but fifth. Interestingly, the analyte that contributed most to biological age prediction was the red cell distribution width (RDW%), with glucose again in second place (Levine et al. 2018):

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Third, Earls et al. (2019) used the Klemera-Doubal algorithm (Klemera and Doubal, 2006) in conjunction with blood test data to predict biological age. Regardless if the blood was analyzed by Labcorp or Quest, higher levels of albumin (the left side of both images below) were associated with the greatest reduction in biological age, up to 5 years! In contrast, HbA1c was associated with a higher biological age when measured by Labcorp (top image, right side), and second to lead in the Quest analysis (bottom image, right side). Interestingly, glucose came in third and fifth in the Labcorb and Quest data sets, respectively, in terms of its positive association with biological age.

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Glucose would’ve been an obvious choice, but would you have guessed that albumin may be just as important, and potentially more important for predicting biological age?

 

If you’re interested, please have a look at my book!

References

Earls JC, Rappaport N, Heath L, Wilmanski T, Magis AT, Schork NJ, Omenn GS, Lovejoy J, Hood L, Price ND. Multi-Omic Biological Age Estimation and Its Correlation With Wellness and Disease Phenotypes: A Longitudinal Study of 3,558 Individuals. J Gerontol A Biol Sci Med Sci. 2019 Nov 13;74(Supplement_1):S52-S60. doi: 10.1093/gerona/glz220.

Klemera P, Doubal S. A new approach to the concept and computation of biological age. Mech Ageing Dev. 2006;127:240–248. doi:10.1016/j. mad.2005.10.004

Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, Hou L, Baccarelli AA, Stewart JD, Li Y, Whitsel EA, Wilson JG, Reiner AP, Aviv A, Lohman K, Liu Y, Ferrucci L, Horvath S. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018 Apr 18;10(4):573-591. doi: 10.18632/aging.101414.

Mamoshina P, Kochetov K, Putin E, Cortese F, Aliper A, Lee WS, Ahn SM, Uhn L, Skjodt N, Kovalchuk O, Scheibye-Knudsen M, Zhavoronkov A. Population specific biomarkers of human aging: a big data study using South Korean, Canadian and Eastern European patient populations. J Gerontol A Biol Sci Med Sci. 2018 Jan 11.

1.7 Years of Biological Aging In The Past 3.6 Years

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In an earlier post (https://michaellustgarten.wordpress.com/2018/06/26/maximizing-health-and-lifespan-is-calorie-restriction-essential/), I documented my aging.ai biologic age for 13 blood test measurements from 2016 – 2019. If you missed that post, here are those data:
agingai2Note that note my average biologic age has slowly increased from 2016 to 2019, from 28y in 2016 (2 measurements), to 29.25y in 2017 (6 measurements), to 29.5y in 2018 (6 measurements), to 30y in my June 2019 measurement.

To gain more insight into my 2019 prediction for biologic age, I kept measuring. On September 17, 2019, I had my worst biological age to date, 33y, based on the blood test data below:
Screen Shot 2019-11-03 at 3.51.05 PM.png

Seeing a biological age that high (for me) was the motivation that I needed to finally stick to a mild caloric restriction, which I hypothesized would positively affect my biological age. I wrote about this in my recent Phenotypic Age post (https://michaellustgarten.wordpress.com/2019/11/01/biological-age-31-3y-chronological-age-46y/). Did it work? Shown below is my blood test data for October 29th.

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Based on that data, my biological age was 28y, and when averaging the 3 measurements in 2019 (so far!), my average biological age is 29.67y. When considering that my average biological age in 2016 was 28y, it looks like I’ve only aged ~1.7 years in 3.58 years of elapsed time!

 

If you’re interested, please have a look at my book!

Optimizing Biological Age: Is Calorie Restriction Essential?

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My goal is to break the world record for lifespan, 122 years, which is currently held by Jean Calment. How do I plan to do that? A good start would be calorie restriction (CR), a diet where you eat 10-30%+ less calories than your normal intake. CR is the gold standard for increasing lifespan in a variety of organisms, including yeast, flies, worms, and rodents (McDonald et al. 2010).

With the goal of maximizing my health and lifespan, in April 2015, I started a CR diet. Inherent in that was weighing all my food and recording it on an online website that tracks macro-and micro-nutrients. From then until March 2016, I was pretty good at keeping my calories relatively low, as I averaged 2302 calories. However, since 3/2016, it’s been exceedingly difficult to keep my calories that low, as I’ve averaged 2557 calories/day. So is having a higher calorie intake worse for my lifespan goal than a lower calorie intake?

Maybe not. In addition to tracking my daily nutrition since 2015, I’ve also had regular blood testing performed. I’ve measured the typical things that you get at a yearly checkup, including the lipid profile (triglycerides, total cholesterol, LDL, HDL, VLDL) markers of kidney and liver  function (BUN, creatinine, uric acid, and ALT, AST, respectively), and the complete blood count (red and white blood cells, and their differentials). By tracking my daily nutrition and circulating biomarkers, I’m able to quickly intervene on any potential aging and disease-related mechanisms by using my diet to optimize my circulating biomarkers.

On my quest for optimal health and lifespan, biological age is more important than my chronological age (I’m 46y). So what’s my biological age? Between 2016-2019, the group at Insilico Medicine published 2 papers that included circulating biomarker data from more than 200,000 people (Putin et al. 2015, Mamoshina et al. 2018) to derive a biological age predictor (aging.ai). So what’s my biological age?

Shown below is my predicted biological age over 13 blood tests from 3/2016 to 6/2019:

agingai2

Although I wasn’t on a CR diet during that time, my average biological age was 29.2 years, which is ~34% younger than my chronological age. Would my biological age be even younger with a lower calorie intake? I’m working on reducing my calorie intake again (it’s not easy for me), so stay tuned for that!

Here are the my biomarker values corresponding to each blood test, for anyone who wants to double check the results:
agingai2 values

References

Mamoshina P, Kochetov K, Putin E, Cortese F, Aliper A, Lee WS, Ahn SM, Uhn L, Skjodt N, Kovalchuk O, Scheibye-Knudsen M, Zhavoronkov A. Population specific biomarkers of human aging: a big data study using South Korean, Canadian and Eastern European patient populations. J Gerontol A Biol Sci Med Sci. 2018 Jan 11.

McDonald RB, Ramsey JJ. Honoring Clive McCay and 75 years of calorie restriction research. J Nutr. 2010 Jul;140(7):1205-10.

Putin E, Mamoshina P, Aliper A, Korzinkin M, Moskalev A, Kolosov A, Ostrovskiy A, Cantor C, Vijg J, Zhavoronkov A. Deep biomarkers of human aging: Application of deep neural networks to biomarker development. Aging (Albany NY). 2016 May;8(5):1021-33.

If you’re interested, please have a look at my book: